Genetic insights into bovine spastic syndrome (Crampy) in Holstein dairy cattle
Bibliographic record
Abstract
estimates ranging from 0.057 to 0.085. The inclusion of genomic data significantly increased the reliability of breeding values by 5% to 17%. Through a GWAS using GCTA software, a total of 41 significant SNPs were found to be significantly associated with Crampy. Functional analysis revealed 44 genes, among which we have highlighted the genes WNK2 (BTA8), DTNBP1 (BTA23), and ADK (BTA28), which have been associated with ion transport, muscle function, and neuron signaling, respectively. Enriched colocated QTL annotations linked to ketosis, muscle calcium content, and muscle zinc content were also identified, highlighting the role of metabolic processes and mineral homeostasis in muscle function. Breeding value correlations between Crampy and production, health, longevity, and type traits, and the selection indices were moderately low but favorable, indicating that current breeding strategies may indirectly select against Crampy. These findings highlight genomic selection as a viable strategy to mitigate Crampy in Canadian dairy herds, emphasizing the need for continued phenotyping for this disorder and optimization of breeding practices to improve animal welfare and sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".